Transcript Consolidated

Consolidated sector data and the
analysis of macroeconomic imbalances
Peter Pontuch
European Commission
DG Economic and Financial Affairs
TF on data consolidation, Luxembourg, April 17-18 2013
Outline
1. The underlying logic of consolidation
a. The accounting perspective
b. The economic perspective
2. Use of sector data for economic analysis
a. Macroeconomic Imbalance Procedure
b. Analytical work
3. The current and the desired states
4. Conclusion
2
Outline
1. The underlying logic of consolidation
a. The accounting perspective
b. The economic perspective
2. Use of sector data for economic analysis
a. Macroeconomic Imbalance Procedure
b. Analytical work
3. The current and the desired states
4. Conclusion
3
The accounting perspective
Consolidated data present the sector as if it were a single entity: only
financial assets, liabilities, and transactions with other sectors are reported.
• Intra-sector assets, liabilities and flows offset each other, whatever their
nature:
• Intra-group lending between a company and its resident subsidiaries,
• “Inter-company” lending defined here as loans between two
independent entities.
4
The accounting perspective:
Intra-sector lending
Intra-group lending:
•
Between the corporate center and its resident subsidiaries,
•
Between peer companies of the same Group.
Inter-company lending:
•
Treasury investments (minor at the aggregate level),
•
Loans to associated companies that are not fully controlled subsidiaries,
•
Loans to customers or suppliers, esp. in a context of the recent credit tightness
(e.g., in the recent period Rolls Royce distributed ~GBP 500m inter-company
loans to strategic suppliers due to tight credit).
5
The accounting perspective
Group A
Company A1
A
L
SE
Independent
company B
A
L
Subsidiary A2 (100%)
A
L
SE
SE
6
The accounting perspective
Group A
In consolidated sector data, the treatment of the
Company A1
A
L
intra-group loan of 50 (red) would be the same
200
as the treatment of the inter-company loan of 30
(green).
Total debt: 450 (non-cons.), 370 (cons.).
SE
50
Independent
company B
A
Subsidiary A2 (100%)
100
L
A
L
150
30
SE
50
SE
30
7
The economic perspective
Consolidated data reflect the amount of external funds received by the sector.
•
These funds allowed additional investment spending (corporate sector) or
consumption (household sector).
•
Effects on economic activity: positive in the upturn phase, potentially negative if
indebtedness needs to be reduced (deleveraging).
•
Relevant for measuring the credit boom-type of imbalances (e.g., IE and ES).
Non-consolidated data also useful: risks coming from the distribution of debt
across the sector.
•
Deleveraging pressures if debt concentrated in some parts of the sector.
•
Possible contagion effects.
•
But, it is necessary to distinguish intra-group and inter-company lending.
8
The economic perspective
Group A
The control of subsidiary A2 makes the intragroup loan relatively benign from an “imbalances”
Company A1
A
L
200
perspective.
Little economic difference with the case where A2
was legally a part of A1.
SE
The intra-group loan was financed by A1, most
50
likely through a corresponding liability (grey).
Subsidiary A2 (100%)
100
L
A
Even if A2 defaults on its liability, A1 remains
liable of the external liability.
50
Non-consolidated data lead to double-counting.
SE
9
The economic perspective
Group A
Company A1
A
L
A2 has little control over company B:
•
How the funds are spent (investment project),
•
Likelihood of repayment.
The loan was financed by A2 (grey). If B defaults:
SE
possible contagion on A2.
Independent
company B
A
Subsidiary A2 (100%)
100
L
A
SE
30
L
150
30
SE
Again, there is double-counting in nonconsolidated data.
But consolidated data do not capture the whole
story (if B defaults there is a risk of contagion).
10
Outline
1. The underlying logic of consolidation
a. The accounting perspective
b. The economic perspective
2. Use of sector data for economic analysis
a. Macroeconomic Imbalance Procedure
b. Analytical work
3. The current and the desired states
4. Conclusion
11
The Macroeconomic Imbalance Procedure
External
Internal
imbalances imbalances
Role and Scope
• External positions (current accounts, net
international investment positions)
• Competitiveness developments (REERs, ULCs)
• Export performance (export market shares)
• Private sector indebtedness (credit, debt)
• Public sector indebtedness
• Assets markets (housing)
• Financial sector developments (as of 2012)
12
MIP: annual cycle
November
Alert
Mechanism
Report
Economic reading of
early warning
scoreboard to
identify Member
States with potential
risks
April
In-depth reviews
Analysis to distinguish between
benign and harmful macroeconomic
developments and to identify policy
options
April/May
Policy
response
No problem
Procedure stops.
Imbalance exists
Commission/Council
recommendations
under Article 121.2
Severe imbalance
Scoreboard
Additional indicators
Scoreboard
Additional indicators
Any other relevant data and
analytical work
Data use
Commission/Council
recommendation
under Article 121.4
Relevance for MIP: consolidated or nonconsolidated?
Excessive private sector debt implies risks for growth and financial
stability and increases the vulnerability to economic shocks.
Consolidated debt determines the amount the sector received from (and
needs to ultimately repay to) other sectors. Relevant for effects on
economic activity (imbalances in the boom years if excessive investment)
and vulnerability to economic shocks (risks of deleveraging in the
adjustment phase).
Non-consolidated debt provides information about the total gross
indebtedness of the sector, acknowledging that some financing may be
intra-sector. Could signal deficiencies in access to finance from the
financial sector, and point to financial stability issues (contagion) and
issues with distribution of debt and assets in the sector.
14
Relevance for MIP: consolidated or nonconsolidated?
Non-consolidated data are available for all MS and less subject to
heterogeneity in national reporting and consolidation practices.
However, non-consolidated data have drawbacks:
•
Contain both intra-group and inter-company loans. The former are not
an imbalance, merely reflecting corporate financing, accounting, and tax
practices.
•
We do not know the relative weight of intra-group transactions within
intra-sector liabilities of MS.
•
The intra-group financing practices (and hence their weight) likely differ
across MS: comparability issues.
15
MIP Scoreboard: The basics
Screening device to identify potential imbalances requiring an in-depth
review.
Selection of 11 indicators with indicative alert thresholds: thresholds
mostly based on quantiles of historical data. Headline indicators
complemented with a set of "additional indicators".
The Alert Mechanism Report presents an economic reading of
indicators, and proposes a list of MS requiring in-depth reviews. The
reading considers other relevant information, over a longer time horizon.
Presented on t-1 annual data but the economic reading considers latest
data available at any frequency.
May be adjusted: As available data and experience evolve, technical
adjustments in the definitions of the variables are possible.
16
MIP Scoreboard as of Nov 2012
Year 2011
3 year average
of Current
Account
Balance as %
of GDP
Net International Investment Position
as % of GDP
% Change (3 years) of
Real Effective
Exchange Rate with
HICP deflators
Thresholds
% Change (5
years) in
Export
Market
Shares
% Change
(3 years) in
Nominal ULC
% y-o-y
change in
deflated
House
Prices
Private Sector
Credit Flow as
% of GDP
Private Sector
Debt as % of
GDP
General
Government
Debt as % of
GDP
Unemployment rate
- 3-year
average
y-o-y % change in
Total Financial
Sector Liabilities,
non-consolidated
data
-4/+6%
-35%
±5% & ±11%
-6%
+9% & +12%
+6%
15%
160%
60%
10%
16.5%
BE
-0.3
65.7
-0.5
-10.2
6.2
-0.1
11.6
236
98
7.8
4.7
BG
-3.4
-85.6
3.1
17.2
20.3
-9.0
-6.7
146
16
9.4
5.6
CZ
-3.0
-49.3
0.3
8.4
3.3
0.0
2.5
78
41
6.9
3.8
DK
5.0
24.5
-1.7
-16.9
4.7
-4.9
-2.2
238
46
7.0
4.7
DE
5.9
32.6
-3.9
-8.4
5.9
1.4
4.8
128
81
6.9
2.1
EE
2.8
-57.8
0.8
11.1
-6.2
3.3
6.8
133
6
14.4
-4.4
IE
0.0
-96.0
-9.1
-12.2
-12.8
-15.2
4.0
310
106
13.3
-0.6
EL
-10.4
-86.1
3.1
-18.7
4.1
-5.1
-5.5
125
171
13.2
-3.4
ES
-4.3
-91.7
-1.3
-7.6
-2.1
-10.0
-4.1
218
69
19.9
3.7
FR
-1.6
-15.9
-3.2
-11.2
6.0
3.8
4.0
160
86
9.6
7.3
IT
-2.9
-20.6
-2.1
-18.4
4.4
-2.0
2.6
129
121
8.2
3.8
CY
-8.4
-71.3
-0.9
-16.4
8.8
-8.5
16.1
288
71
6.6
-0.2
LV
3.1
-73.3
-0.6
23.6
-15.0
4.9
-2.5
125
42
18.1
-4.5
LT
0.0
-52.6
3.6
25.2
-8.4
2.4
-0.8
70
39
15.6
8.9
LU
7.5
107.8
0.8
-10.1
12.5
1.5
2.5
326
18
4.8
11.3
HU
0.6
-105.9
-3.3
-2.8
3.7
-4.1
6.4
167
81
10.7
-2.6
MT
-4.3
5.7
-3.0
11.7
5.8
-2.3
2.2
210
71
6.8
1.4
NL
7.5
35.5
-1.6
-8.2
5.8
-4.0
0.7
225
66
4.2
7.2
AT
2.2
-2.3
-1.0
-12.7
5.9
-8.0
4.1
161
72
4.4
-0.3
PL
-4.6
-63.5
-10.9
12.8
4.3
-5.7
7.1
80
56
9.2
4.4
PT
-9.1
-105.0
-1.9
-9.5
0.9
-3.6
-3.2
249
108
11.9
-0.7
RO
-4.3
-62.5
-2.4
22.8
12.9
-18.9
1.8
72
33
7.2
4.3
SI
-0.4
-41.2
-0.3
-6.1
8.3
1.0
1.9
128
47
7.1
-1.3
SK
-2.1
-64.4
4.3
20.9
4.4
-5.6
3.3
76
43
13.4
1.2
FI
0.6
13.1
-1.3
-22.9
9.1
-0.3
4.6
179
49
8.1
30.8
SE
6.6
-8.3
3.9
-11.6
1.2
1.0
6.3
232
38
8.1
3.6
UK
-2.2
-17.3
-7.1
-24.2
8.1
-5.4
1.0
205
85
7.8
8.5
Additional indicators as of Nov 2012
Alert Mechanism Report 2012: private
indebtedness as a prominent issue
The AMR provides an economic reading of the latest Scoreboard for
all EU27 MS, considering the indicators' evolution over time, as well as
additional indicators.
The 2012 AMR discusses private debt in more detail in 16 MS. In 2
cases of high private indebtedness (non-consolidated), the findings were
qualified by the effect of inter-company loans on the levels of debt.
The AMR selected 14 MS for an In-depth review (private debt issues
mentioned to some extent in all 14):
Belgium, Bulgaria, Denmark, Spain, France, Italy, Cyprus, Hungary,
Malta, Netherlands, Slovenia, Finland, Sweden and the United
Kingdom.
19
In-depth reviews 2013 and private debt
On April 10 2013 the Commission published 13 IDRs.
• In 11 cases there was a specific focus on private debt (BG, BE, ES,
FR, HU, MT, NL, FI, SE, SI, UK), generally based on the headline nonconsolidated private debt data.
• In 10 cases the analysis was either complemented with
consolidated data or qualified by intra-sector lending practices.
• Additional country-specific issues were also raised:
• Increase in account payable financing (BG), corporate tax
optimization practices (BE, SE), special-purpose entities (HU), crossborder lending (SE, FI, UK).
20
Example: Belgian IDR 2013
Non-consolidated private debt at 237% of GDP in 2011 (3rd in EU).
• Large part due to NFCs: 182.5pp vs. 99pp in the euro area.
• Consolidated debt of NFCs only at 89.4pp vs. 81.4pp in the euro area.
The large difference is due to intragroup lending practices (financial centres).
• Allowance for Corporate Equity policy introduced in 2006 encourages
triangular schemes between group financing entities and subsidiaries.
Assessment: The risks of high corporate indebtedness are attenuated by
the underlying factors. The cost of these practices is statistical noise and
reduced tax revenues.
21
Example: Belgian IDR 2013
Debt Decomposition, All Sectors, NonConsolidated
Debt Decomposition, All Sectors, Consolidated
Source: Commission services. Note: * indicates estimated figure using quarterly data.
22
Analytical work:
A study on private deleveraging
The Commission recently published the study Indebtedness, Deleveraging
Dynamics and Macroeconomic Adjustment (European Economy - Economic
Papers 477, April 2013).
Four aims:
1. Identification of deleveraging pressures in the private sector;
2. Quantification of these pressures;
3. Refining the message using credit supply and demand conditions;
4. Simulation of the impact of a household deleveraging shock.
23
Identification of deleveraging pressures
Challenge: examine and summarize several alternative indicators of
indebtedness.
Approach: Composite indicators based on clustering and PCA methods.
•Two dimensions: debt to capacity to repay and debt to assets. For each we
use alternative definitions of indebtedness ratios (GDP or GOS/GDI for the
former, assets or deflated assets for the latter).
•Focus on current levels of debt as well as accumulation over 2000-2008.
•The main analysis uses non-consolidated data (availability, consistency with
MIP).
•Robustness check using consolidated data for NFCs confirms the findings for
24
all MS, except BE (intra-sector lending).
Identification of deleveraging pressures for
non-financial corporates
Non-financial corporates sector deleveraging
pressures considering the capacity to repay
Non-financial corporates sector deleveraging
pressures considering assets
2
1.5
ES CY
BG
PT
0.5
EE
RO
LV
0
IT
LT
-0.5
PL
-1
-1.5
HU
UK
DKSI
BE
SE
EA17
FI FR
AT
EL
DE
EL
1.5
Debt accumulation, 2000-2008
Debt accumulation, 2000-2008
IE
1
1
IT SI
0.5
AT
0
-0.5
NL
NL
EE
PT
FI
UK
IE LT
SE EA17
BE
DK
PL
SK
CY
HU
DE
FR
CZ
LV
ES
BG
RO
SK
CZ
-1
-0.5
0
0.5
Debt level, 2011
1
1.5
-1
-1
-0.5
0
0.5
Debt level, 2011
1
1.5
25
Identification of deleveraging pressures for
non-financial corporates
Composite indicator on deleveraging pressures for EU27 Member
States, Non-financial corporates
1
EL
0.9
Composite II: Debt/Assets
0.8
0.7
LV
0.6
SI
IT
ES
0.5
RO
0.4
LT
0.3
SK
0.2
PL
CZ
EE
FI
EA17
DE
AT
DK
FR
BG
PT
UK
IE
SE
BE
CY
HU
NL
0.1
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Composite I: Debt/Capacity to repay
0.8
0.9
1
Main finding: Deleveraging pressures in the NFC sector identified for: BE, BG, CY, EL, ES, HU, IE, IT, PT, SI,
SE, UK, EE, LV.
26
Outline
1. The underlying logic of consolidation
a. The accounting perspective
b. The economic perspective
2. Use of sector data for economic analysis
a. Macroeconomic Imbalance Procedure
b. Analytical work
3. The current and the desired states
4. Conclusion
27
Availability: not there yet!
• Currently, annual consolidated data available for all EU27 except UK. Quarterly
consolidated data are more problematic.
• Back in 2011, the incompleteness of annual (and absence of quarterly)
consolidated data was one of the arguments against using them as the headline
indicator in the MIP Scoreboard.
• They nevertheless serve as additional indicator.
• But…
• Availability (i.e. being able to get a data point from the ESTAT database) is not
everything, since there are reasonable doubts about reliability of these data.
28
Plausibility: what you see and what you get
300
• Difference between non-consolidated
and consolidated NFC debt (AF3 and
Non-consolidated and consolidated NFC debt
(AF3, AF4), % of GDP
250
Non-consolidated
AF4) is in many cases very small.
• In EA27 the difference between NC
Consolidated
100
90
Difference (RHS)
80
70
200
60
and C debt ranges from 0 pp to 93
pp.
50
150
• Some of this heterogeneity is
real.
• Some is probably due to
40
100
30
20
50
inconsistent practices, especially
in the grey zone and beyond…
• Even worse, this throws doubt even
on the quality of NC data. Does NC
mean the same thing everywhere?
10
0
0
BE LU SE MT IE PT FI FR HU DE AT ES SI BG LV CY CZ LT PL IT NL RO EE DK EL SK UK
Plausible
Source: ESTAT
Grey zone
Implausible
29
Consistency: how bad is it?
• What we know is that national consolidation practices differ.
• We do not know:
• What is the order of magnitude of the discrepancies generated
by different practices?
• Do we have clusters of MS with comparable consolidation
practices?
• How consistent were the practices over time? Are historical data
series reliable?
30
Country specificities: noise or patterns?
• Even with consistent consolidation practices across all MS, some
country-specific differences will continue to affect the
comparability of C/NC figures:
• Depth of corporate groups and intra-group financing;
• Cross-border financing of foreign subsidiaries;
• Financial engineering practices (e.g., SPEs and tax
optimization).
• A strong need to know more about these issues.
31
Problems with the current state
• Due to the issues discussed, our current analysis of private balance
sheets relies more heavily on non-consolidated data.
• Consolidated data are used as a qualifier, if they are available
and if they "look plausible".
• This is not optimal, as both C and NC (and the gap) are relevant
for the analysis of macroeconomic imbalances.
• The quality of data that we use is not clear.
• The plausibility criterion is insufficient.
• Can we trust at least the NC data?
32
The ideal state
• Transparent and consistent consolidation rules applied
homogeneously across EU27.
• Both current and historical data.
• Even in that case one needs additional information about:
1. The extent of intra-group lending which is a noise in NC data
(for our purposes),
2. Multinational HQs and their foreign subsidiary lending,
3. Effects of SPEs.
• At least occasional insights on these three topics would be
extremely helpful.
33
Conclusions
• Our current analysis uses primarily non-consolidated data, complemented by
consolidated data when available.
• Consistence and quality of the consolidated figures is not completely clear.
• Both consolidated and non-consolidated data would be useful for the analysis
of macroeconomic imbalances.
• Ideally: a set of common transparent and consistent consolidation rules applied in
all EU27.
• Both current and historical data.
• Additional insights into intra-group lending, foreign subsidiary lending, SPEs
would be also very useful.
34
Thank you!
Backup
Macroeconomic Imbalance Procedure: context
• MIP introduced as part of the Six-Pack in late 2011:
• Turbulent economic circumstances–sovereign crises and poor
growth
• High uncertainty/stress in financial markets
• Significant risks of negative spillovers, especially in the euro area
• Large stocks of imbalances from the pre-crisis period
• Significant but still incomplete adjustment
• Incomplete institutional framework
37
MIP Scoreboard, thresholds
External imbalances and competitiveness
Indicator
3-year average
of current
account
balance
as a %
of GDP
Data
source
EUROSTAT
(Balance of
Payments
statistics)
Indicativ
e
threshold
s
-4/+6%
Lower quartile
(also used as a
reference for
upper threshold)
Period
for
calculatin
g
threshold
s
Some
Additional
indicator
s to be
used in
economic
reading
1970-2007
Net
lending/borrowi
ng vis-à-vis
ROW (CA+KA)
as % of GDP
Net
International
Investment
Position as a
%
of GDP
EUROSTAT
(Balance of
Payments
Statistics),.
% change
(3 years) of
Real Effective
Exchange
Rate, HICP
deflators
relative to 35
industrial
countries (a)
DG ECFIN
(data base
Price and Cost
competitivenes
s).
Internal imbalances
% change
(5 years) in
export market
shares
% change
(3 years) in
nominal unit
labour cost (b)
EUROSTAT
(Balance of
Payments
Statistics),.
EUROSTAT
(National
Accounts)
private sector
debt
as %
of GDP (d), (e)
general
government
debt
as %
of GDP
(f)
y-o-y %
change in
Total
Financial
Sector
Liabilities,
nonconsolidated
data
EUROSTAT
(Labour Force
Survey)
,
EUROSTAT
(National
Accounts)
EUROSTAT
(EDP – treaty
definition).
,
EUROSTAT
(National
Accounts)
+15%
Upper
Quartile
+10%
160%
Upper
Quartile
+60%
16.5%
1994-2007
1994-2007
1991-2007
Private sector
debt based on
consolidated
data
Debt over
equity ratio
y-o-y %
change in
deflated house
prices (c)
private sector
credit flow
as %
of GDP (d), (e)
EUROSTAT,.
, EUROSTAT
(National
Accounts)
+6%
Upper quartile
-35%
Lower quartile
+/-5% for €A
+/-11% non€A
Lower and
Upper
Quartiles of
EA -/+ s.d. of
EA
-6%
Lower quartile
+9% €A
+12% non-€A
Upper
Quartile €A
+3%
First available
year (mid1990s)-2007
1995-2007
1995-2007
1995-2007
First year
available-2007
1995-2007
REER vis-à-vis
rest of the euro
area
Export market
shares based on
volumes of
goods; Labour
productivity;
Trend TFP
growth
Nominal ULCs
(changes over
1, 5, 10 years);
Effective ULC
relative to the
rest of euroarea
Real house
price changes
(cumulated
over 3 years);
Nominal house
price index
Value-added in
residential
construction
Change in
private debt
Net External
Debt as %
GDP
unemployment rate
- 3-year
average